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AMDO
2008
Springer
13 years 7 months ago
A Generative Model for Motion Synthesis and Blending Using Probability Density Estimation
The main focus of this paper is to present a method of reusing motion captured data by learning a generative model of motion. The model allows synthesis and blending of cyclic moti...
Dumebi Okwechime, Richard Bowden
CVPR
2005
IEEE
14 years 7 months ago
Mixture Trees for Modeling and Fast Conditional Sampling with Applications in Vision and Graphics
We introduce mixture trees, a tree-based data-structure for modeling joint probability densities using a greedy hierarchical density estimation scheme. We show that the mixture tr...
Frank Dellaert, Vivek Kwatra, Sang Min Oh
WSCG
2001
108views more  WSCG 2001»
13 years 6 months ago
Co-Operative and Concurrent Blending Motion Generators
In this paper we will be describing a new animation architecture and its implementation in our system LIVE. This model introduces a new blending layer approach which uses several ...
Vincent Bonnafous, Eric Menou, Jean-Pierre Jessel,...
CVPR
2004
IEEE
14 years 7 months ago
Model-Based Motion Clustering Using Boosted Mixture Modeling
Model-based clustering of motion trajectories can be posed as the problem of learning an underlying mixture density function whose components correspond to motion classes with dif...
Vladimir Pavlovic
ICCV
2007
IEEE
14 years 6 months ago
Conditional State Space Models for Discriminative Motion Estimation
We consider the problem of predicting a sequence of real-valued multivariate states from a given measurement sequence. Its typical application in computer vision is the task of mo...
Minyoung Kim, Vladimir Pavlovic